Improving Wastewater Management for Sustainable Environmental Conditions: A Flexible Semantic Network-Based Approach

Anthropogenic activities interact through multifactorial processes that generate harmful factors, hindering wastewater management (WWM) and causing environmental degradation, particularly in rapidly urbanizing coastal regions. Understanding how these processes operate is essential for identifying effective interventions under data-limited conditions. This study introduces a process-based and context-driven approach whose main contribution lies in the construction of semantic pathways that represent how indirect anthropogenic drivers give rise to direct harmful factors affecting WWM and the environmental state. Semantic networks are used as a formal representation tool to model these pathways, where nodes represent factors and directed arcs represent causal relationships. Harmful semantic pathways are evaluated within a multidisciplinary decision-making framework supported by multi-criteria decision-making (MCDM) methods that account for environmental, social, economic, and sustainability criteria. The approach is applied to a coastal tourist municipality on the Mexican Pacific coast, where rapid urban expansion and insufficient basic services have severely constrained wastewater management and contributed to environmental damage. Results show that constructing and analyzing semantic pathways enables decision-makers to identify critical harmful factors and prioritize viable pro-environmental actions. The resulting priorities (range 0–1) highlight the restoration of wastewater treatment plants and improved urban planning as the most effective interventions, followed by mangrove reforestation and changes in agricultural practices. The proposed approach supports transparent, context-sensitive decision-making and is transferable to coastal tourist municipalities facing similar wastewater management challenges.